{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:59:23Z","timestamp":1777658363057,"version":"3.51.4"},"reference-count":27,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,7,10]],"date-time":"2018-07-10T00:00:00Z","timestamp":1531180800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>Diabetic Retinopathy is the most prevalent cause of avoidable vision impairment, mainly affecting the working-age population in the world. Recent research has given a better understanding of the requirement in clinical eye care practice to identify better and cheaper ways of identification, management, diagnosis and treatment of retinal disease. The importance of diabetic retinopathy screening programs and difficulty in achieving reliable early diagnosis of diabetic retinopathy at a reasonable cost needs attention to develop computer-aided diagnosis tool. Computer-aided disease diagnosis in retinal image analysis could ease mass screening of populations with diabetes mellitus and help clinicians in utilizing their time more efficiently. The recent technological advances in computing power, communication systems, and machine learning techniques provide opportunities to the biomedical engineers and computer scientists to meet the requirements of clinical practice. Diverse and representative retinal image sets are essential for developing and testing digital screening programs and the automated algorithms at their core. To the best of our knowledge, IDRiD (Indian Diabetic Retinopathy Image Dataset), is the first database representative of an Indian population. It constitutes typical diabetic retinopathy lesions and normal retinal structures annotated at a pixel level. The dataset provides information on the disease severity of diabetic retinopathy, and diabetic macular edema for each image. This makes it perfect for development and evaluation of image analysis algorithms for early detection of diabetic retinopathy.<\/jats:p>","DOI":"10.3390\/data3030025","type":"journal-article","created":{"date-parts":[[2018,7,10]],"date-time":"2018-07-10T09:24:01Z","timestamp":1531214641000},"page":"25","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":760,"title":["Indian Diabetic Retinopathy Image Dataset (IDRiD): A Database for Diabetic Retinopathy Screening Research"],"prefix":"10.3390","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2268-7504","authenticated-orcid":false,"given":"Prasanna","family":"Porwal","sequence":"first","affiliation":[{"name":"Center of Excellence in Signal and Image Processing, Department of Electronics and Telecommunication Engineering, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded 431606, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5226-6706","authenticated-orcid":false,"given":"Samiksha","family":"Pachade","sequence":"additional","affiliation":[{"name":"Center of Excellence in Signal and Image Processing, Department of Electronics and Telecommunication Engineering, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded 431606, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7400-7040","authenticated-orcid":false,"given":"Ravi","family":"Kamble","sequence":"additional","affiliation":[{"name":"Center of Excellence in Signal and Image Processing, Department of Electronics and Telecommunication Engineering, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded 431606, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6947-4090","authenticated-orcid":false,"given":"Manesh","family":"Kokare","sequence":"additional","affiliation":[{"name":"Center of Excellence in Signal and Image Processing, Department of Electronics and Telecommunication Engineering, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded 431606, India"}]},{"given":"Girish","family":"Deshmukh","sequence":"additional","affiliation":[{"name":"Eye Clinic, Sushrusha Hospital, Nanded 431601, India"}]},{"given":"Vivek","family":"Sahasrabuddhe","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Shankarrao Chavan Government Medical College, Nanded 431606, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8656-9913","authenticated-orcid":false,"given":"Fabrice","family":"Meriaudeau","sequence":"additional","affiliation":[{"name":"Centre for Intelligent Signal and Imaging Research, Department of Electrical &amp; Electronic Engineering, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Malaysia"}]}],"member":"1968","published-online":{"date-parts":[[2018,7,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Reichel, E., and Salz, D. (2015). Diabetic retinopathy screening. Managing Diabetic Eye Disease in Clinical Practice, Springer.","DOI":"10.1007\/978-3-319-08329-2_3"},{"key":"ref_2","unstructured":"International Diabetes Federation (IDF) (2017). IDF Diabetes Atlas, IDF."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1159\/000320075","article-title":"Diabetic macular edema","volume":"Volume 47","author":"Bandello","year":"2010","journal-title":"Macular Edema"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2653","DOI":"10.2337\/diacare.26.9.2653","article-title":"Diabetic retinopathy and diabetic macular edema: Pathophysiology, screening, and novel therapies","volume":"26","author":"Ciulla","year":"2003","journal-title":"Diabetes Care"},{"key":"ref_5","unstructured":"International Council of Ophthalmology (ICO) (2017). Guidelines for Diabetic Eye Care, International Council of Ophthalmology (ICO). [2nd ed.]."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e339","DOI":"10.1016\/S2214-109X(13)70113-X","article-title":"Causes of vision loss worldwide, 1990\u20132010: A systematic analysis","volume":"1","author":"Bourne","year":"2013","journal-title":"Lancet Glob. Health"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"16012","DOI":"10.1038\/nrdp.2016.12","article-title":"Diabetic Retinopathy","volume":"2","author":"Wong","year":"2016","journal-title":"Nat. Rev. Disease Prim."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1109\/RBME.2010.2084567","article-title":"Retinal imaging and image analysis","volume":"3","author":"Garvin","year":"2010","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Jelinek, H., and Cree, M.J. (2009). Automated Image Detection of Retinal Pathology, CRC Press.","DOI":"10.1201\/9781420037005"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1111\/j.1464-5491.2009.02870.x","article-title":"Diabetic retinopathy screening: A systematic review of the economic evidence","volume":"27","author":"Jones","year":"2010","journal-title":"Diabet. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1111\/ceo.12745","article-title":"Addressing risk factors, screening, and preventative treatment for diabetic retinopathy in developing countries: A review","volume":"44","author":"Lin","year":"2016","journal-title":"Clin. Exp. Ophthalmol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"69","DOI":"10.4103\/0301-4738.178150","article-title":"Diabetic retinopathy: An epidemic at home and around the world","volume":"64","author":"Raman","year":"2016","journal-title":"Indian J. Ophthalmol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Porwal, P., Pachade, S., Kokare, M., Deshmukh, G., and Sahasrabuddhe, V. (2018). Automatic Retinal Image Analysis for the Detection of Diabetic Retinopathy. Biomedical Signal and Image Processing in Patient Care, IGI Global.","DOI":"10.4018\/978-1-5225-2829-6.ch008"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1111\/ceo.12696","article-title":"Diabetic retinopathy: global prevalence, major risk factors, screening practices and public health challenges: A review","volume":"44","author":"Ting","year":"2016","journal-title":"Clin. Exp. Ophthalmol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1236","DOI":"10.1109\/TMI.2002.806290","article-title":"A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina","volume":"21","author":"Walter","year":"2002","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Shortliffe, E.H., and Blois, M.S. (2006). The computer meets medicine and biology: Emergence of a discipline. Biomedical Informatics, Springer.","DOI":"10.1007\/0-387-36278-9_1"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.preteyeres.2005.07.001","article-title":"Retinal image analysis: Concepts, applications and potential","volume":"25","author":"Patton","year":"2006","journal-title":"Prog. Retin. Eye Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3546","DOI":"10.1167\/iovs.12-10347","article-title":"Validating retinal fundus image analysis algorithms: Issues and a proposal","volume":"54","author":"Trucco","year":"2013","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"ref_19","unstructured":"Porwal, P., Pachade, S., Kamble, R., Kokare, M., Deshmukh, G., Sahasrabuddhe, V., and Meriaudeau, F. (2018). Indian Diabetic Retinopathy Image Dataset (IDRiD). IEEE DataPort."},{"key":"ref_20","unstructured":"Porwal, P., Pachade, S., Kamble, R., Kokare, M., Deshmukh, G., Sahasrabuddhe, V., MacGillivray, T., Sidib\u00e9, D., Giancardo, L., and Quellec, G. (2018, July 02). Diabetic Retinopathy Segmentation and Grading Challenge. Available online: https:\/\/idrid.grand-challenge.org\/."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1111\/j.1469-7580.2005.00395.x","article-title":"Retinal vascular image analysis as a potential screening tool for cerebrovascular disease: A rationale based on homology between cerebral and retinal microvasculatures","volume":"206","author":"Patton","year":"2005","journal-title":"J. Anat."},{"key":"ref_22","unstructured":"Advanced Concepts in Imaging Software (ADCIS) (2018, July 02). Aphelion Image Annotator. Available online: http:\/\/www.adcis.net\/en\/Image-Processing-And-Analysis-Software-And-Custom-Engineering-Developments.html."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.irbm.2013.01.010","article-title":"TeleOphta: Machine learning and image processing methods for teleophthalmology","volume":"34","author":"Cazuguel","year":"2013","journal-title":"Irbm"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"290","DOI":"10.4239\/wjd.v4.i6.290","article-title":"Classification of diabetic retinopathy and diabetic macular edema","volume":"4","author":"Wu","year":"2013","journal-title":"World J. Diabetes"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1177\/193229680900300315","article-title":"EyePACS: an adaptable telemedicine system for diabetic retinopathy screening","volume":"3","author":"Cuadros","year":"2009","journal-title":"J. Diabetes Sci. Technol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.media.2011.07.004","article-title":"Exudate-based diabetic macular edema detection in fundus images using publicly available datasets","volume":"16","author":"Giancardo","year":"2012","journal-title":"Med. Image Anal."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"231","DOI":"10.5566\/ias.1155","article-title":"Feedback on a publicly distributed image database: The Messidor database","volume":"33","author":"Zhang","year":"2014","journal-title":"Image Anal. Stereol."}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/3\/3\/25\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:11:17Z","timestamp":1760195477000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/3\/3\/25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,10]]},"references-count":27,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2018,9]]}},"alternative-id":["data3030025"],"URL":"https:\/\/doi.org\/10.3390\/data3030025","relation":{},"ISSN":["2306-5729"],"issn-type":[{"value":"2306-5729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7,10]]}}}